Literature DB >> 33999812

Design and Preliminary Performance Assessment of a Wearable Tremor Suppression Glove.

Yue Zhou, Anas Ibrahim, Kenneth G Hardy, Mary E Jenkins, Michael D Naish, Ana Luisa Trejos.   

Abstract

Approximately 25% of individuals living with parkinsonian tremor do not respond to traditional treatments. Wearable tremor suppression devices (WTSD) provide an alternative approach, however, tremor in the fingers has not been given as much attention as tremor in the elbow and the wrist. Therefore, the objective of this study is to design a wearable tremor suppression glove that can suppress tremor simultaneously, but independently, in multiple hand joints without restricting the user's voluntary motion.
METHODS: A WTSD was designed for managing tremor in the index finger metacarpophalangeal (MCP) joint, thumb MCP joint, and the wrist. The prototype was tested and assessed on a participant living with parkinsonian tremor.
RESULTS: The experimental evaluation showed an overall suppression of 73.1%, 80.7%, and 85.5% in resting tremor, 70.2%, 79.5%, and 81% in postural tremor, and 60.0%, 58.7%, and 65.0% in kinetic tremor in the index finger MCP joint, the thumb MCP joint, and the wrist, respectively.
CONCLUSION: This first assessment of a WTSD for people living with Parkinson's disease provides confirmation of the feasibility of the approach. The next step requires a comprehensive validation on a broader population in order to evaluate the performance of the WTSD. SIGNIFICANCE: This study demonstrates the feasibility of using a WTSD to manage hand and finger tremor. The device enriches the field of upper-limb tremor management, as the first WTSD for multiple joints of the hand.

Entities:  

Year:  2021        PMID: 33999812     DOI: 10.1109/TBME.2021.3080622

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  2 in total

1.  Survey-based identification of design requirements and constraints for a wearable tremor suppression device.

Authors:  Yue Zhou; Devin Box; Kenneth G Hardy; Mary E Jenkins; Jayne Garland; Michael D Naish; Ana Luisa Trejos
Journal:  J Rehabil Assist Technol Eng       Date:  2022-05-07

2.  Using Deep Learning for Task and Tremor Type Classification in People with Parkinson's Disease.

Authors:  Ghazal Farhani; Yue Zhou; Mary E Jenkins; Michael D Naish; Ana Luisa Trejos
Journal:  Sensors (Basel)       Date:  2022-09-27       Impact factor: 3.847

  2 in total

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